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At least 91 records · Page 5Linked to original sources
USGS2015

Formulating the American Geophysical Union's Scientific Integrity and Professional Ethics Policy: Challenges and lessons learned

Creating an ethics policy for a large, diverse geosciences organization is a challenge, especially in the midst of the current contentious dialogue in the media related to such issues as climate change, sustaining natural resources, and responding to natural hazards. In 2011, the American Geophysical Union (AGU) took on this challenge, creating an Ethics Task Force to update their ethics policies to better support their new Strategic Plan and respond to the changing scientific research environment. Dialogue with AGU members and others during the course of creating the new policy unveiled some of the following issues to be addressed. Scientific results and individual scientists are coming under intense political and public scrutiny, with the efficacy of the science being questioned. In some cases, scientists are asked to take sides and/or provide opinions on issues beyond their research, impacting their objectivity. Pressure related to competition for funding and the need to publish high quality and quantities of papers has led to recent high-profile plagiarism, data fabrication, and conflict of interest cases. The complexities of a continuously advancing digital environment for conducting, reviewing, and publishing science has raised concerns over the ease of plagiarism, fabrication, falsification, inappropriate peer review, and the need for better accessibility of data and methods. Finally, students and scientists need consistent education and encouragement on the importance of ethics and integrity in scientific research. The new AGU Scientific Integrity and Ethics Policy tries to address these issues and provides an inspirational code of conduct to encourage a responsible, positive, open, honest scientific research environment.

Book chapter↗
USGS2024

Chapter 24 - Resilience-based challenges and opportunities for fisheries management in Anthropocene rivers

Few pristine rivers remain worldwide, as they are among the most anthropogenically modified ecosystems. We suggest the geomorphology , hydrology and ecology of Anthropocene rivers are fundamentally different from historical natural rivers. These changes challenge conventional fisheries management practices, suggesting the tools supporting fisheries management may require expansion so that strategies match the scope and scale of present-day problems. We believe that resilience-thinking concepts offer substantial benefits for fisheries managers in Anthropocene rivers. When viewing resilience as a property of an ecosystem, the focus should be increasing the capacity of the system to self-organise and adapt to withstand regime shifts from internal and external disturbances. As an approach, a resilience-based perspective favours managing for sustainability and stewardship of fisheries by placing an emphasis on enhancing the capacity of complex systems to cope with dynamic change. Three case studies presented herein use resilience thinking to highlight challenges and opportunities for fisheries management in Anthropocene rivers from Europe, North America and Australia. Ultimately, a resilience approach to fisheries management emphasises increasing the ecological, institutional and societal capacities to deal with change, whether those changes be hydroclimatic, geomorphic, biological or social, to sustain desirable subsistence, recreational and commercial fisheries.

Book chapter↗
USGS2026

The future for reptiles: Advances and challenges in the Anthropocene

The future for the Reptilia will be one of continued discovery of the extant diversity of species in every group and continued challenges for their conservation. Most species will persist, albeit in smaller and increasingly fragmented geographic ranges, and active conservation measures can help to ensure survival of highly vulnerable species. There are more than 12,440 documented species of reptiles, up from 10,500 only seven years ago. Transfer of laboratory techniques, computational resources, and access to literature to herpetologists throughout the world is fueling the increase in systematic studies of reptiles. The bulk of reptiles are the squamates, lizards and snakes, with impressive diversity on most continents. Habitat loss, landscape fragmentation, exploitation, invasive species, environmental contamination, and global warming are persistent challenges to all biodiversity, including reptiles. Endemism, ecological specialization, and restricted ranges generally make species more vulnerable to anthropogenic disturbances. Moreover, the natural history information that is so important for informing conservation aims is lacking for most newly described forms, whether they represent completely novel discoveries or result from taxonomic revisions. The major lineages of reptiles exhibit enormous variation in life history traits, ranging from extremely long-lived species with low fecundity to those with short generation times and high fecundity. Reptiles vary in their degree of ecological specialization, and many live in difficult-to-sample habitats. It is implausible, if not impossible, to gather detailed information on thousands of species of reptiles, many of which are secretive and difficult to study. However, evaluating where species are likely to fit along life history gradients of time to maturity, brood size, and frequency of reproduction reveals much about their abilities to persist in the face of anthropogenic disturbance. Combined with information on geographic distribution and the severity of anthropogenic pressures, consideration of life history strategies reveals important implications for conservation of reptile species. Modern approaches to conservation of reptiles, including conservation translocations, regulation of the international trade in reptiles, management of imperiled species in the context of landscapes, progress in confronting emerging diseases, and resolving human-wildlife conflict in all its forms can help ensure the persistence of the great diversity of the Reptilia in the Anthropocene.

Book chapter↗
USGS2011

Common challenges for ecological modelling: synthesis of facilitated discussions held at the symposia organized for the 2009 conference of the International Society for Ecological Modelling in Quebec City, Canada, (October 6-9, 2009)

The eleven symposia organized for the 2009 conference of the International Society for Ecological Modelling (ISEM 2009) held in Quebec City, Canada, October 6–9, 2009, included facilitated discussion sessions following formal presentations. Each symposium focused on a specific subject, and all the subjects could be classified into three broad categories: theoretical development, population dynamics and ecosystem processes. Following discussions with the symposia organizers, which indicated that they all shared similar issues and concerns, the facilitated discussions were task-oriented around four basic questions: (1) key challenges in the research area, (2) generating and sharing new ideas, (3) improving collaboration and networking, and (4) increasing visibility to decision-makers, partners and clients. Common challenges that emerged from the symposia included the need for improved communication and collaboration among different academic disciplines, further progress in both theoretical and practical modelling approaches, and accentuation of technology transfer. Regarding the generation and sharing of new ideas, the main issue that emerged was the type of positive interactions that should be encouraged among potential collaborators. The usefulness of the Internet, particularly for the sharing of open-source software and conducting discussion forums, was highlighted for improving collaboration and networking. Several communication tools are available today, and it is important for modellers to use them more intensively. Visibility can be increased by publishing professional newsletters, maintaining informal contacts with the public, organizing educational sessions in primary and secondary schools, and developing simplified analytical frameworks and pilot studies. Specific issues raised in each symposium are also discussed.

Ecological Modelling↗
USGS2026

Cumulative effects analysis to inform public land management in the United States: Key characteristics and legal challenges

Considering potential cumulative effects of proposed actions is fundamental to environmental impact analysis. However, cumulative effects analyses historically are not robust, especially for site-specific decisions. We sought to identify opportunities to strengthen cumulative effects analysis in a large United States public land management agency, the Bureau of Land Management (BLM). We asked 1) how cumulative effects analyses were legally challenged, 2) how site-specific cumulative effects analyses aligned with policy and compared to the broader-scale analyses to which they tiered, and 3) whether characteristics of cumulative effects analyses varied with category of proposed action, type of resource, or agency office. We used thematic analysis to assess litigation and appeals case documents finalized from 2010 to 2020 and a set of document analysis questions to assess National Environmental Policy Act (NEPA) analyses for BLM decisions completed prior to 2020 in Alaska and Colorado. We found that legal challenges related to cumulative effects focused on absence of cumulative effects analysis. In NEPA analyses, cumulative effects were frequently considered, but elements recommended in policy, such as citations, methods, and scope, were rarely included. These elements were present more often in the broader analyses to which site-specific analyses tiered. Many elements of cumulative effects analyses varied by proposed action and BLM office, and analyses of potential cumulative effects on air quality were consistently more detailed than for other resources. Our results suggest that many problems that historically plagued cumulative effects analysis persist. Advances in methods, training, and guidance could strengthen the defensibility of NEPA analyses.

Alaska, Colorado↗
USGS2005

The challenges associated with developing science-based landscape scale management plans

Planning activities over large landscapes poses a complex of challenges when trying to balance the implementation of a conservation strategy while still allowing for a variety of consumptive and nonconsumptive uses. We examine a case in southeast Alaska to illustrate the breadth of these challenges and an approach to developing a science-based resource plan. Not only was the planning area, the Tongass National Forest, USA, exceptionally large (approximately 17 million acres or 6.9 million ha), but it also is primarily an island archipelago environment. The water system surrounding and going through much of the forest provides access to facilitate the movement of people, animals, and plants but at the same time functions as a barrier to others. This largest temperate rainforest in the world is an exceptional example of the complexity of managing at such a scale but also illustrates the role of science in the planning process. As we enter the 21st century, the list of questions needing scientific investigation has not only changed dramatically, but the character of the questions also has changed. Questions are contentious, cover broad scales in space and time, and are highly complex and interdependent. The provision of unbiased and objective information to all stakeholders is an important step in informed decision-making.

Landscape and Urban Planning↗
USGS2016

VNTR diversity in Yersinia pestis isolates from an animal challenge study reveals the potential for in vitro mutations during laboratory cultivation

Underlying mutation rates and other evolutionary forces shape the population structure of bacteria in nature. Although easily overlooked, similar forces are at work in the laboratory and may influence observed mutations. Here, we investigated tissue samples and Yersinia pestis isolates from a rodent laboratory challenge with strain CO92 using whole genome sequencing and multi-locus variable-number tandem repeat (VNTR) analysis (MLVA). We identified six VNTR mutations that were found to have occurred in vitro during laboratory cultivation rather than in vivo during the rodent challenge. In contrast, no single nucleotide polymorphism (SNP) mutations were observed, either in vivo or in vitro . These results were consistent with previously published mutation rates and the calculated number of Y. pestis generations that occurred during the in vitro versus the in vivo portions of the experiment. When genotyping disease outbreaks, the potential for in vitro mutations should be considered, particularly when highly variable genetic markers such as VNTRs are used.

Infection, Genetics and Evolution↗
USGS2022

Understanding rates of change: A case study using fossil pollen records from California to assess the potential for and challenges to a regional data synthesis

Insights into the rates at which ecosystems and vegetation respond to a changing climate is fundamental to anticipating impacts of projected climate change. Characterization of vegetation change over millennia to centuries has potential to make an important contribution toward this goal, and regional scale syntheses of fossil pollen data can provide the foundation for this understanding. However, challenges of data analysis and integration are nontrivial. Here we present a case study in which publicly available fossil pollen data for California are assessed and analyzed. The data are selected according to a clearly defined selection criteria, and a Rate of Change (RoC) value is calculated to assess rates of vegetation change in California from ~15k BP (before A.D. 1950) to the present. Our results highlight several challenges presented by the extant data sets, including temporal sampling variation within and between records, large age control uncertainties, and sparse, geographically biased coverage. Recommendations for methodological refinements to better characterize ecological rates of change include increasing sampling frequency, maintaining a consistent temporal spacing within records, and applying probabilistic approaches to existing pollen data sets.

California↗
USGS2015

On the reconstruction of palaeo-ice sheets: Recent advances and future challenges

Reconstructing the growth and decay of palaeo-ice sheets is critical to understanding mechanisms of global climate change and associated sea-level fluctuations in the past, present and future. The significance of palaeo-ice sheets is further underlined by the broad range of disciplines concerned with reconstructing their behaviour, many of which have undergone a rapid expansion since the 1980s. In particular, there has been a major increase in the size and qualitative diversity of empirical data used to reconstruct and date ice sheets, and major improvements in our ability to simulate their dynamics in numerical ice sheet models. These developments have made it increasingly necessary to forge interdisciplinary links between sub-disciplines and to link numerical modelling with observations and dating of proxy records. The aim of this paper is to evaluate recent developments in the methods used to reconstruct ice sheets and outline some key challenges that remain, with an emphasis on how future work might integrate terrestrial and marine evidence together with numerical modelling. Our focus is on pan-ice sheet reconstructions of the last deglaciation, but regional case studies are used to illustrate methodological achievements, challenges and opportunities. Whilst various disciplines have made important progress in our understanding of ice-sheet dynamics, it is clear that data-model integration remains under-used, and that uncertainties remain poorly quantified in both empirically-based and numerical ice-sheet reconstructions. The representation of past climate will continue to be the largest source of uncertainty for numerical modelling. As such, palaeo-observations are critical to constrain and validate modelling. State-of-the-art numerical models will continue to improve both in model resolution and in the breadth of inclusion of relevant processes, thereby enabling more accurate and more direct comparison with the increasing range of palaeo-observations. Thus, the capability is developing to use all relevant palaeo-records to more strongly constrain deglacial (and to a lesser extent pre-LGM) ice sheet evolution. In working towards that goal, the accurate representation of uncertainties is required for both constraint data and model outputs. Close cooperation between modelling and data-gathering communities is essential to ensure this capability is realised and continues to progress.

Quaternary Science Reviews↗
USGS2026

Fifty years of riverine harmful algal bloom modeling: A global synthesis of approaches, challenges, and opportunities

This systematic literature review critically examines 162 articles on harmful algal bloom (HAB) modeling in riverine systems to uncover persistent gaps, redefine critical challenges, and propose trackable opportunities to advance future modeling efforts. Articles largely focused on site-specific applications (93%) across more than 80 rivers worldwide. Most modeled systems were large, eutrophic rivers with flow modifications or obstructions. Geographic clustering of modeled systems was pronounced, with South Korea accounting for 26% of articles, followed by Europe (25%), United States (21%), and China (12%). Modeling approaches were led by process-based models (59%), though use of data-driven models (37%) increased over time, reflecting advances in computing and monitoring technology. Modeling endpoints varied widely across the articles with many focused on gross measures of algal abundance and fewer representing more refined endpoints like algal toxins or community composition. Furthermore, inconsistent units and taxonomic resolution hindered comparability between models. Datasets used for model development and calibration typically spanned 5 years, with weekly to monthly sampling at 1–10 sites, though durations and site counts were positively skewed. Quantitative metrics of model skill were often absent and included a diverse set of metrics when reported. Across all models, nutrients, light availability, streamflow, algal physiological processes, and water temperature emerged as key predictors, though algal processes were rarely incorporated in data-driven models. Scenario analyses primarily were conducted with process-based models and addressed flow management, whereas forecasting applications were less common and typically used data-driven models. After almost 50 years of riverine HAB modeling, persistent challenges include underrepresentation of benthic habitats, neglect of side-channel and backwater influences, insufficient documentation of river features, and weak linkages between modeled endpoints and potential harms. Addressing these gaps through reporting of contextual information, models from other aquatic settings, benchmark datasets, and community-driven tools could advance riverine HAB modeling towards increased transferability and ultimately operational forecasts.

Water Research↗
USGS2011

Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges

Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty

Journal of Geophysical Research: Biogeosciences↗
USGS2023

Water, water everywhere, but every drop unique: Emerging challenges in the science to understand the role of contaminants in management of drinking water supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

GeoHealth↗
USGS2018

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Proceedings of the National Academy of Sciences of↗
USGS2013

Empirical estimates to reduce modeling uncertainties of soil organic carbon in permafrost regions: a review of recent progress and remaining challenges

The vast amount of organic carbon (OC) stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. However, estimates of the quantity, decomposability, and combustibility of OC contained in permafrost-region soils remain highly uncertain, thereby limiting our ability to predict the release of greenhouse gases due to permafrost thawing. Substantial differences exist between empirical and modeling estimates of the quantity and distribution of permafrost-region soil OC, which contribute to large uncertainties in predictions of carbon–climate feedbacks under future warming. Here, we identify research challenges that constrain current assessments of the distribution and potential decomposability of soil OC stocks in the northern permafrost region and suggest priorities for future empirical and modeling studies to address these challenges.

Environmental Research Letters↗
USGS2019

Confronting models with data: The challenges of estimating disease spillover

For pathogens known to transmit across host species, strategic investment in disease control requires knowledge about where and when spillover transmission is likely. One approach to estimating spillover is to directly correlate observed spillover events with covariates. An alternative is to mechanistically combine information on host density, distribution, and pathogen prevalence to predict where and when spillover events are expected to occur. We use several case studies at the wildlife-livestock disease interface to highlight the challenges, and potential solutions, to estimating spatio-temporal variation in spillover risk. Datasets on multiple host species often do not align in space, time or resolution, and may have no estimates of observation error. Linking these datasets requires they be related to a common spatial and temporal resolution and appropriately propagating errors in predictions can be difficult. Hierarchical models are one potential solution, but for fine-resolution predictions at broad spatial scales many models become computationally challenging. Despite these limitations, the confrontation of mechanistic predictions with observed events is an important avenue for developing a better understanding of pathogen spillover. Systems where data have been collected at all levels in the spillover process are rare, or non-existent, and require investment and sustained effort across disciplines.

Philosophical Transactions of the Royal Society B:↗
USGS2025

Challenges and opportunities for data integration to improve estimation of migratory connectivity

Understanding migratory connectivity, or the linkage of populations between seasons, is critical for effective conservation and management of migratory wildlife. A growing number of tools are available for understanding where migratory individuals and populations occur throughout the annual cycle. Integration of the diverse measures of migratory movements can help elucidate migratory connectivity patterns with methodology that accounts for differences in sampling design, directionality, effort, precision and bias inherent to each data type. The R package MigConnectivity was developed to estimate population-specific connectivity and the range-wide strength of those connections. New functions allow users to integrate intrinsic markers, tracking and long-distance reencounter data, collected from the same or different individuals, to estimate population-specific transition probabilities (estTransition) and the range-wide strength of those transition probabilities (estStrength). We used simulation and real-world case studies to explore the challenges and limitations of data integration based on data from three migratory bird species, Painted Bunting ( Passerina ciris ), Yellow Warbler ( Setophaga petechia ) and Bald Eagle ( Haliaeetus leucocephalus ), two of which had bidirectional data. We found data integration is useful for quantifying migratory connectivity, as single data sources are less likely to be available across the species range. Furthermore, accurate strength estimates can be obtained from either breeding-to-nonbreeding or nonbreeding-to-breeding data. For bidirectional data, integration can lead to more accurate estimates when data are available from all regions in at least one season. The ability to conduct combined analyses that account for the unique limitations and biases of each data type is a promising possibility for overcoming the challenge of range-wide coverage that has been hard to achieve using single data types. The best-case scenario for data integration is to have data from all regions, especially if the question is range-wide or data are bidirectional. Multiple data types on animal movements are becoming increasingly available and integration of these growing datasets will lead to a better understanding of the full annual cycle of migratory animals.

Methods in Ecology and Evolution↗
USGS2024

Climate-smart invasive species management for 21st century global change challenges

Addressing the global challenges of climate change and biotic invasions requires understanding their interactions and implications for natural resource management. To facilitate and support invasive species management in a changing climate, we review how climate change and invasions interact to impact the planning, action, and outcomes of invasive species management. Climate change is affecting which species natural resource managers need to assess, monitor, and target by facilitating the introduction of new potential invasive species and altering pathways of introduction and spread. Climate-driven shifts in seasonal conditions and phenological events disrupt and require more flexible management timelines. Climate change may reduce the efficacy and feasibility of current treatment methods and create a need to shift management goals as native ecosystems become more vulnerable to disturbance. Additionally, extreme climate events can compound the spread and impacts of biological invasions, making invasive species management a necessary part of extreme event preparation and response planning. As a solution to these challenges, we propose climate-smart invasive species management, which we define as the approaches that managers and decision-makers can take to address the interactive effects of climate change and invasions. Climate-smart invasive species management includes considering shifts in species ranges, abundance, and impacts to inform monitoring, treatment, and regulation of potential and new invaders at multiple scales. Managers can also adjust the timing of and approach to treatment as efficacy and feasibility change, promote resilient ecosystems through climate-smart restoration, and consider the effects of climate change when setting management goals. Furthermore, climate adaptation funds could expand avenues of funding and support for invasive species management. Explicitly considering the interactions of climate change and biological invasions within organizational decision-making and policy will lead to more effective management and can promote more resilient landscapes.

Global Change Biology↗
USGS2017

Grand challenges in understanding the interplay of climate and land changes

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Earth Interactions↗